Il ruolo delle architetture di controllo nella progettazione e sviluppo di applicazioni web: Un confronto fra event-loop e control-loop utilizzando il linguaggio dart e linguaggi agent-oriented

Quando si parla di architetture di controllo in ambito Web, il Modello ad Eventi è indubbiamente quello più diffuso e adottato. L’asincronicità e l’elevata interazione con l’utente sono caratteristiche tipiche delle Web Applications, ed un architettura ad eventi, grazie all’adozione del suo tipico ciclo di controllo chiamato Event Loop, fornisce un'astrazione semplice ma sufficientemente espressiva per soddisfare tali requisiti. La crescita di Internet e delle tecnologie ad esso associate, assieme alle recenti conquiste in ambito di CPU multi-core, ha fornito terreno fertile per lo sviluppo di Web Applications sempre più complesse. Questo aumento di complessità ha portato però alla luce alcuni limiti del modello ad eventi, ancora oggi non del tutto risolti. Con questo lavoro si intende proporre un differente approccio a questa tipologia di problemi, che superi i limiti riscontrati nel modello ad eventi proponendo un architettura diversa, nata in ambito di IA ma che sta guadagno popolarità anche nel general-purpose: il Modello ad Agenti. Le architetture ad agenti adottano un ciclo di controllo simile all’Event Loop del modello ad eventi, ma con alcune profonde differenze: il Control Loop. Lo scopo di questa tesi sarà dunque approfondire le due tipologie di architetture evidenziandone le differenze, mostrando cosa significa affrontare un progetto e lo sviluppo di una Web Applications avendo tecnologie diverse con differenti cicli di controllo, mettendo in luce pregi e difetti dei due approcci.

Programmazione di sistemi multi-agente: la piattaforma Jason come caso di studio

L’obiettivo principale di questo elaborato è di mostrare in un primo momento i concetti fondamentali che stanno alla base del paradigma ad agenti. Una volta introdotti, essi verranno collocati in un determinato ambiente di programmazione attraverso una piattaforma specifica chiamata Jason. Come sarà facile capire dalla lettura di questa trattazione, un sistema ad agenti è costituito dagli agenti stessi e dall’ambiente in cui sono situati. L’ambiente risulta quindi un altro tassello fondamentale ed è stato introdotto allo scopo un nuovo paradigma per la programmazione di ambienti chiamato Agent & Artifact. Nello specifico, verrà ampiamente descritto il framework di riferimento di tale paradigma: CArtAgO. Dopo aver illustrato i concetti e gli strumenti per poter agilmente programmare e progettare sistemi ad agenti, verrà infine mostrato un esempio di applicazione di tale tecnologia attraverso un case study. Il progetto del sistema in questione riguarda un reale caso aziendale e integra la tecnologia RFID con quella ad agenti per fornire la soluzione ad un problema noto come quello del controllo periodico delle scorte.

Learning for sustainability - LforS: Simulation games - a creative tool for interactive learning

Description of simulation and training games as tool for awareness and capacity development in multi steakeholder processes

Critical issues in managing protected areas by multi-stakeholder participation - analysis of a process in the Swiss Alps

Balancing the frequently conflicting priorities of conservation and economic development poses a challenge to management of the Swiss Alps Jungfrau-Aletsch World Heritage Site (WHS). This is a complex societal problem that calls for a knowledge-based solution. This in turn requires a transdisciplinary research framework in which problems are defined and solved cooperatively by actors from the scientific community and the life-world. In this article we re-examine studies carried out in the region of the Swiss Alps Jungfrau-Aletsch WHS, covering three key issues prevalent in transdisciplinary settings: integration of stakeholders into participatory processes; perceptions and positions; and negotiability and implementation. In the case of the Swiss Alps Jungfrau-Aletsch WHS the transdisciplinary setting created a situation of mutual learning among stakeholders from different levels and backgrounds. However, the studies showed that the benefits of such processes of mutual learning are continuously at risk of being diminished by the power play inherent in participatory approaches.

Learning Two-Person Interaction Models for Responsive Synthetic Humanoids

Imitation learning is a promising approach for generating life-like behaviors of virtual humans and humanoid robots. So far, however, imitation learning has been mostly restricted to single agent settings where observed motions are adapted to new environment conditions but not to the dynamic behavior of interaction partners. In this paper, we introduce a new imitation learning approach that is based on the simultaneous motion capture of two human interaction partners. From the observed interactions, low-dimensional motion models are extracted and a mapping between these motion models is learned. This interaction model allows the real-time generation of agent behaviors that are responsive to the body movements of an interaction partner. The interaction model can be applied both to the animation of virtual characters as well as to the behavior generation for humanoid robots.

Constructing a user experience user experience-based mobile learning environment

Mobile learning, in the past defined as learning with mobile devices, now refers to any type of learning-on-the-go or learning that takes advantage of mobile technologies. This new definition shifted its focus from the mobility of technology to the mobility of the learner (O'Malley and Stanton 2002; Sharples, Arnedillo-Sanchez et al. 2009). Placing emphasis on the mobile learner’s perspective requires studying “how the mobility of learners augmented by personal and public technology can contribute to the process of gaining new knowledge, skills, and experience” (Sharples, Arnedillo-Sanchez et al. 2009). The demands of an increasingly knowledge based society and the advances in mobile phone technology are combining to spur the growth of mobile learning. Around the world, mobile learning is predicted to be the future of online learning, and is slowly entering the mainstream education. However, for mobile learning to attain its full potential, it is essential to develop more advanced technologies that are tailored to the needs of this new learning environment. A research field that allows putting the development of such technologies onto a solid basis is user experience design, which addresses how to improve usability and therefore user acceptance of a system. Although there is no consensus definition of user experience, simply stated it focuses on how a person feels about using a product, system or service. It is generally agreed that user experience adds subjective attributes and social aspects to a space that has previously concerned itself mainly with ease-of-use. In addition, it can include users’ perceptions of usability and system efficiency. Recent advances in mobile and ubiquitous computing technologies further underline the importance of human-computer interaction and user experience (feelings, motivations, and values) with a system. Today, there are plenty of reports on the limitations of mobile technologies for learning (e.g., small screen size, slow connection), but there is a lack of research on user experience with mobile technologies. This dissertation will fill in this gap by a new approach in building a user experience-based mobile learning environment. The optimized user experience we suggest integrates three priorities, namely a) content, by improving the quality of delivered learning materials, b) the teaching and learning process, by enabling live and synchronous learning, and c) the learners themselves, by enabling a timely detection of their emotional state during mobile learning. In detail, the contributions of this thesis are as follows: • A video codec optimized for screencast videos which achieves an unprecedented compression rate while maintaining a very high video quality, and a novel UI layout for video lectures, which together enable truly mobile access to live lectures. • A new approach in HTTP-based multimedia delivery that exploits the characteristics of live lectures in a mobile context and enables a significantly improved user experience for mobile live lectures. • A non-invasive affective learning model based on multi-modal emotion detection with very high recognition rates, which enables real-time emotion detection and subsequent adaption of the learning environment on mobile devices. The technology resulting from the research presented in this thesis is in daily use at the School of Continuing Education of Shanghai Jiaotong University (SOCE), a blended-learning institution with 35.000 students.

Digital Systems for Open Access to Formal and Informal Learning

Today, Digital Systems and Services for Technology Supported Learning and Education are recognized as the key drivers to transform the way that individuals, groups and organizations “learn” and the way to “assess learning” in 21st Century. These transformations influence: Objectives - moving from acquiring new “knowledge” to developing new and relevant “competences”; Methods – moving from “classroom” based teaching to “context-aware” personalized learning; and Assessment – moving from “life-long” degrees and certifications to “on-demand” and “in-context” accreditation of qualifications. Within this context, promoting Open Access to Formal and Informal Learning, is currently a key issue in the public discourse and the global dialogue on Education, including Massive Open Online Courses (MOOCs) and Flipped School Classrooms. This volume on Digital Systems for Open Access to Formal and Informal Learning contributes to the international dialogue between researchers, technologists, practitioners and policy makers in Technology Supported Education and Learning. It addresses emerging issues related with both theory and practice, as well as, methods and technologies that can support Open Access to Formal and Informal Learning. In the twenty chapters contributed by international experts who are actively shaping the future of Educational Technology around the world, topics such as: - The evolution of University Open Courses in Transforming Learning - Supporting Open Access to Teaching and Learning of People with Disabilities - Assessing Student Learning in Online Courses - Digital Game-based Learning for School Education - Open Access to Virtual and Remote Labs for STEM Education - Teachers’ and Schools’ ICT Competence Profiling - Web-Based Education and Innovative Leadership in a K-12 International School Setting are presented. An in-depth blueprint of the promise, potential, and imminent future of the field, Digital Systems for Open Access to Formal and Informal Learning is necessary reading for researchers and practitioners, as well as, undergraduate and postgraduate students, in educational technology.

Code-specific learning rules improve action selection by populations of spiking neurons

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Sequential incoherence in a multi-party synchronous computer mediated communication for an introductory Health Informatics course.

Online courses will play a key role in the high-volume Informatics education required to train the personnel that will be necessary to fulfill the health IT needs of the country. Online courses can cause feelings of isolation in students. A common way to address these feelings is to hold synchronous online "chats" for students. Conventional chats, however, can be confusing and impose a high extrinsic cognitive load on their participants that hinders the learning process. In this paper we present a qualitative analysis that shows the causes of this high cognitive load and our solution through the use of a moderated chat system.

Sustainable Wastewater Management: Is it Possible to Regulate Micropollution in the Future by Learning from the Past? A Policy Analysis

This paper applies a policy analysis approach to the question of how to effectively regulate micropollution in a sustainable manner. Micropollution is a complex policy problem characterized by a huge number and diversity of chemical substances, as well as various entry paths into the aquatic environment. It challenges traditional water quality management by calling for new technologies in wastewater treatment and behavioral changes in industry, agriculture and civil society. In light of such challenges, the question arises as to how to regulate such a complex phenomenon to ensure water quality is maintained in the future? What can we learn from past experiences in water quality regulation? To answer these questions, policy analysis strongly focuses on the design and choice of policy instruments and the mix of such measures. In this paper, we review instruments commonly used in past water quality regulation. We evaluate their ability to respond to the characteristics of a more recent water quality problem, i.e., micropollution, in a sustainable way. This way, we develop a new framework that integrates both the problem dimension (i.e., causes and effects of a problem) as well as the sustainability dimension (e.g., long-term, cross-sectoral and multi-level) to assess which policy instruments are best suited to regulate micropollution. We thus conclude that sustainability criteria help to identify an appropriate instrument mix of end-of-pipe and source-directed measures to reduce aquatic micropollution.

Multi-phase postmortem CT angiography: recognizing technique-related artefacts and pitfalls

BACKGROUND AND PURPOSE Multi-phase postmortem CT angiography (MPMCTA) is increasingly being recognized as a valuable adjunct medicolegal tool to explore the vascular system. Adequate interpretation, however, requires knowledge about the most common technique-related artefacts. The purpose of this study was to identify and index the possible artefacts related to MPMCTA. MATERIAL AND METHODS An experienced radiologist blinded to all clinical and forensic data retrospectively reviewed 49 MPMCTAs. Each angiographic phase, i.e. arterial, venous and dynamic, was analysed separately to identify phase-specific artefacts based on location and aspect. RESULTS Incomplete contrast filling of the cerebral venous system was the most commonly encountered artefact, followed by contrast agent layering in the lumen of the thoracic aorta. Enhancement or so-called oedematization of the digestive system mucosa was also frequently observed. CONCLUSION All MPMCTA artefacts observed and described here are reproducible and easily identifiable. Knowledge about these artefacts is important to avoid misinterpreting them as pathological findings.

The mini-clinical evaluation exercise during medical clerkships: are learning needs and learning goals aligned?

OBJECTIVES The generation of learning goals (LGs) that are aligned with learning needs (LNs) is one of the main purposes of formative workplace-based assessment. In this study, we aimed to analyse how often trainer–student pairs identified corresponding LNs in mini-clinical evaluation exercise (mini-CEX) encounters and to what degree these LNs aligned with recorded LGs, taking into account the social environment (e.g. clinic size) in which the mini-CEX was conducted. METHODS Retrospective analyses of adapted mini-CEX forms (trainers’ and students’ assessments) completed by all Year 4 medical students during clerkships were performed. Learning needs were defined by the lowest score(s) assigned to one or more of the mini-CEX domains. Learning goals were categorised qualitatively according to their correspondence with the six mini-CEX domains (e.g. history taking, professionalism). Following descriptive analyses of LNs and LGs, multi-level logistic regression models were used to predict LGs by identified LNs and social context variables. RESULTS A total of 512 trainers and 165 students conducted 1783 mini-CEXs (98% completion rate). Concordantly, trainer–student pairs most often identified LNs in the domains of ‘clinical reasoning’ (23% of 1167 complete forms), ‘organisation/efficiency’ (20%) and ‘physical examination’ (20%). At least one ‘defined’ LG was noted on 313 student forms (18% of 1710). Of the 446 LGs noted in total, the most frequently noted were ‘physical examination’ (49%) and ‘history taking’ (21%). Corresponding LNs as well as social context factors (e.g. clinic size) were found to be predictors of these LGs. CONCLUSIONS Although trainer–student pairs often agreed in the LNs they identified, many assessments did not result in aligned LGs. The sparseness of LGs, their dependency on social context and their partial non-alignment with students’ LNs raise questions about how the full potential of the mini-CEX as not only a ‘diagnostic’ but also an ‘educational’ tool can be exploited.

A novel blood-sparing agent in cardiac surgery? First in-patient experience with the synthetic serine protease inhibitor MDCO-2010: a phase II, randomized, double-blind, placebo-controlled study in patients undergoing coronary artery bypass grafting with cardiopulmonary bypass

BACKGROUND Antifibrinolytics have been used for 2 decades to reduce bleeding in cardiac surgery. MDCO-2010 is a novel, synthetic, serine protease inhibitor. We describe the first experience with this drug in patients. METHODS In this phase II, double-blind, placebo-controlled study, 32 patients undergoing isolated primary coronary artery bypass grafting with cardiopulmonary bypass were randomly assigned to 1 of 5 increasing dosage groups of MDCO-2010. The primary aim was to evaluate pharmacokinetics (PK) with assessment of plasmatic concentrations of the drug, short-term safety, and tolerance of MDCO-2010. Secondary end points were influence on coagulation, chest tube drainage, and transfusion requirements. RESULTS PK analysis showed linear dosage-proportional correlation between MDCO-2010 infusion rate and PK parameters. Blood loss was significantly reduced in the 3 highest dosage groups compared with control (P = 0.002, 0.004 and 0.011, respectively). The incidence of allogeneic blood product transfusions was lower with MDCO-2010 4/24 (17%) vs 4/8 (50%) in the control group. MDCO-2010 exhibited dosage-dependent antifibrinolytic effects through suppression of D-dimer generation and inhibition of tissue plasminogen activator-induced lysis in ROTEM analysis as well as anticoagulant effects demonstrated by prolongation of activated clotting time and activated partial thromboplastin time. No systematic differences in markers of end organ function were observed among treatment groups. Three patients in the MDCO-2010 groups experienced serious adverse events. One patient experienced intraoperative thrombosis of venous grafts considered possibly related to the study drug. No reexploration for mediastinal bleeding was required, and there were no deaths. CONCLUSIONS This first-in-patient study demonstrated dosage-proportional PK for MDCO-2010 and reduction of chest tube drainage and transfusions in patients undergoing primary coronary artery bypass grafting. Antifibrinolytic and anticoagulant effects were demonstrated using various markers of coagulation. MDCO-2010 was well tolerated and showed an acceptable initial safety profile. Larger multi-institutional studies are warranted to further investigate the safety and efficacy of this compound.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.